Can we make a chatbot that UNDERSTANDS not just answer questions based on his database?
This question has been studied academically for decades, and is really an extension of the work on Philosophy of Mind that was done in the two or three centuries before that.

A good resource is Mind Design II, though it's getting a little bit old now.

The modern schools of thought are:


Cognitivism. This is in decline, but was extremely popular in the 70's and 80's, and still fairly widespread in one form or another in the AI research community. It says that human brains really are just computers. If they're just computers, and that they're probably running a sort of symbolic reasoning algorithm like unification (although I think it's hard to find anyone who really thinks it's unification anymore). This is the idea underpinning work like SOAR. The main bottleneck, as Drayfus pointed out in the 1970's, is that you need to write down all the facts about something for a machine to "understand" it. "All the facts" turns out to rapidly turn into an infinite number for anything more complex than the smallest "microworlds" that you could deploy an AI program in. Searle also proposed his Chinese Room argument in response to this group, but it holds for Connectionist approaches as well (more on that later...).
Connectionism The connectionists hold that the complexity of our brains comes from massively parallel computation consisting of messages passed between billions of neurons in our heads. They think the correct approach to general AI is likely to involve simulations of similar architectures. It turns out that many of the things that are incredibly hard for Cognitivist projects (e.g. vision), are easy to solve with these approaches. The main criticisms from Cognitivists are that we don't have a very good idea of what these things are doing, and so the claim that they help us understand intelligence is false, and using them to solve practical problems might be dangerous. These are both somewhat fair, in my view. Older Cognitivist arguments, put forth most elegantly by Jerry Fodor, have now been discredited. Fodor argued that properties like language could never be understood as statistical artifacts of parallel computation, but he was wrong: all the best computational systems for language are now connectionist, and no one's ever made a cognitivist one that's even half as convincing. This is the dominant paradigm behind most of the modern advances in the field. Hinton's work forms the basis of most of the recent advances.
Dynamics Searle's argument was rooted in the idea that mapping inputs to outputs couldn't be what's happening in our heads, and that such a system couldn't be called intelligent. This also seems to be an implicit assumption in your question. The Dynamicists believe a variety of things, but I'd characterize them as collectively rejecting this idea. Authors like Paul Churchland argue that Searle's argument is rooted in a sort of pre-enlightenment "folk psychology". It's a bit like the theories that predated modern chemistry. Everyone was sure that fire was a substance that lived inside wood. If you heated up the wood properly, it could get out of the wood, making more heat. On the surface this seems pretty reasonable, but of course, it's wrong: The fire is actually a mixture of the wood with oxygen in the air, forming a new gas. There's no fire inside the wood. Similarly, Churchland would argue that there's no "Consciousness" inside us, allowing us to control our actions in the way we popularly imagine. Subjective experience is more likely to be "along for the ride", and entirely or mostly separate from the intelligent behaviors we observe. Some researchers think it could be described by a sub-system that maps observations of what the rest of the brain does into "stories" for the rest of the brain to receive as a sort of summary digest. Active research in this area tends to focus on things like the insect metaphor, and the interaction of the machine with its environment. It was fairly popular in the 1990's, but the phenominal success of connectionist approaches in the 2000's has led to its decline. Probably the best known experiments were the work of Rodney Brooks.